install.packages(“twitteR”)

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

consumer_key <- “dbWfi30JzOldr4AsLMPvcnDGY” consumer_secret <- “TFPD60ipk3WG3qE0oygJuCURMkpJyFH3YHg5QpJzQBDHxC720M” access_token <- “929140086951706624-zAPjLf53DTFe8ygdCSaYwLpL2TUcl1g” access_secret <- “7HmS3Ebql0xaEa2Urwj8OW64p1jCw0j13uplNTDzf87LJ”

twitteR::setup_twitter_oauth(consumer_key, consumer_secret, access_token, access_secret)

statuses = twitteR::searchTwitter(“terrorism”,n=100000000000,since=‘2010-01-01’,geocode=‘37.09024,-95.712891,1650mi’) #twitteR::getTrends(23424977)

Including Plots

You can also embed plots, for example:

data=read.csv(header=T,file = "Data.csv")

for (i in 1:ncol(data)) {
  boxplot(data$Twitter ~ data[, i],xlab=names(data)[i])
}

chisq.test(data$Twitter,data$weaptype1_txt)

## Warning in chisq.test(data$Twitter, data$weaptype1_txt): Chi-squared
## approximation may be incorrect

## 
##  Pearson's Chi-squared test
## 
## data:  data$Twitter and data$weaptype1_txt
## X-squared = 20.33, df = 4, p-value = 0.0004298

par(mar=c(10,6,4,2)+0.1,mgp=c(5,1,0))


myData <- aggregate(data$Twitter,
    by = list(weapon = data$weaptype1_txt),
    FUN = function(x) c(mean = mean(x), sd = sd(x),
                        n = length(x)))
myData <- do.call(data.frame, myData)
myData$se <- myData$x.sd / sqrt(myData$x.n)



barCenters = barplot(height = myData$x.mean,
                  names.arg = myData$weapon,
                  beside = true, las = 2,
                  ylim = c(0, 1),
                  cex.names = 0.75, 
                  main = "Weapon Type",
                  ylab = "Trending on Twitter",
                  #xlab = "Weapon Type",
                  border = "black", axes = TRUE,
                  las=2,axisnames = TRUE)


segments(barCenters, myData$x.mean - myData$se * 2, barCenters,
         myData$x.mean + myData$se * 2, lwd = 1.5)

arrows(barCenters, myData$x.mean - myData$se * 2, barCenters,
       myData$x.mean + myData$se * 2, lwd = 1.5, angle = 90,
       code = 3, length = 0.05)

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

chisq.test(data$Twitter,data$targtype1_txt)

## Warning in chisq.test(data$Twitter, data$targtype1_txt): Chi-squared
## approximation may be incorrect

## 
##  Pearson's Chi-squared test
## 
## data:  data$Twitter and data$targtype1_txt
## X-squared = 22.474, df = 12, p-value = 0.03254

par(mar=c(8,6,4,2)+0.1,mgp=c(5,1,0))

myData <- aggregate(data$Twitter,
    by = list(target = data$targtype1_txt),
    FUN = function(x) c(mean = mean(x), sd = sd(x),
                        n = length(x)))
myData <- do.call(data.frame, myData)
myData$se <- myData$x.sd / sqrt(myData$x.n)



barCenters = barplot(height = myData$x.mean,
                  names.arg = myData$target,
                  beside = true, las = 2,
                  ylim = c(0, 1),
                  cex.names = 0.6,
                  main = "Target Type",
                  ylab = "Trending on Twitter",
                  border = "black")


segments(barCenters, myData$x.mean - myData$se * 2, barCenters,
         myData$x.mean + myData$se * 2, lwd = 1.5)

arrows(barCenters, myData$x.mean - myData$se * 2, barCenters,
       myData$x.mean + myData$se * 2, lwd = 1.5, angle = 90,
       code = 3, length = 0.05)

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

chisq.test(data$Twitter,data$attacktype1_txt)

## Warning in chisq.test(data$Twitter, data$attacktype1_txt): Chi-squared
## approximation may be incorrect

## 
##  Pearson's Chi-squared test
## 
## data:  data$Twitter and data$attacktype1_txt
## X-squared = 28.003, df = 5, p-value = 3.635e-05

par(mar=c(10,6,4,2)+0.1,mgp=c(5,1,0))

myData <- aggregate(data$Twitter,
    by = list(target = data$attacktype1_txt),
    FUN = function(x) c(mean = mean(x), sd = sd(x),
                        n = length(x)))
myData <- do.call(data.frame, myData)
myData$se <- myData$x.sd / sqrt(myData$x.n)



barCenters = barplot(height = myData$x.mean,
                  names.arg = myData$target,
                  beside = true, las = 2,
                  ylim = c(0, 1),
                  cex.names = 0.6,
                  main = "Attack Type",
                  ylab = "Trending on Twitter",
                  border = "black")


segments(barCenters, myData$x.mean - myData$se * 2, barCenters,
         myData$x.mean + myData$se * 2, lwd = 1.5)

arrows(barCenters, myData$x.mean - myData$se * 2, barCenters,
       myData$x.mean + myData$se * 2, lwd = 1.5, angle = 90,
       code = 3, length = 0.05)

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

## Warning in arrows(barCenters, myData$x.mean - myData$se * 2, barCenters, :
## zero-length arrow is of indeterminate angle and so skipped

RRT

R Markdown

install.packages(“twitteR”)

Including Plots